This series of files compile all analyses done during Chapter 3:
- Section 1 presents the calculation of the indices of exposure.
- Section 2 presents variable exploration and regressions results.
- Section 3 presents species distribution models.
All analyses have been done with R 4.0.2.
Click on the table of contents in the left margin to assess a specific analysis.
Click on a figure to zoom it
Sources of activity considered for the analyses:
- aquaculture influence: AquaInf
- city influence: CityInf
- industries influence: InduInf
- dredging collecting zones: CollDred
- dredging dumping zones: DumpDred
- commercial ships mooring site: MoorShip
- commercial ships traffic routes: TrafShip
- rainwater sewers: RainSew
- wastewater sewers: WastSew
- city wharves: CityWha
- industries wharves: InduWha
Fisheries data considered for the analyses (expressed as number of fishing events or kilograms of collected individuals for each gear):
| Trap |
TrapFish |
2010-2015 |
1061 |
Buccinum sp., Cancer irroratus, Chionoecetes opilio, Homarus americanus |
| Bottom-trawl |
TrawFish |
2013-2014 |
2 |
Pandalus borealis |
| Net |
NetFish |
2010 |
5 |
Clupea harengus, Gadus morhua |
| Dredge |
DredFish |
2010-2014 |
21 |
Mactromeris polynyma |
1. Spatial variation of exposure indices
Here, we compute semivariograms for each exposure index (on the whole raster, not only extracted values at the stations).
AquaInf
## Model selected: Lin
## nugget = 0; sill = 0.00409; range = 1.98608; kappa = 0.5

CityInf
## Model selected: Lin
## nugget = 0; sill = 0.03491; range = 8.85176; kappa = 0.5

InduInf
## Model selected: Lin
## nugget = 0; sill = 0.04594; range = 7.94625; kappa = 0.5

CollDred
## Model selected: Exp
## nugget = 0.00115; sill = 0.00567; range = 6.36284; kappa = 0.5

DumpDred
## Model selected: Lin
## nugget = 0; sill = 0.0084; range = 1.14583; kappa = 0.5

MoorShip
## Model selected: Lin
## nugget = 0; sill = 0.07595; range = 3.05577; kappa = 0.5

TrafShip
## Model selected: Exp
## nugget = 0; sill = 0.22432; range = 3.01617; kappa = 0.5

RainSew
## Model selected: Lin
## nugget = 0; sill = 0.01386; range = 7.93527; kappa = 0.5

WastSew
## Model selected: Sph
## nugget = 0; sill = 0.0132; range = 23.19017; kappa = 0.5

CityWha
## Model selected: Exp
## nugget = 0; sill = 0.01242; range = 7.08521; kappa = 0.5

InduWha
## Model selected: Sph
## nugget = 0.00029; sill = 0.0083; range = 5.59199; kappa = 0.5

TrapFish
## Model selected: Lin
## nugget = 0.00033; sill = 0.00125; range = 1.13171; kappa = 0.5

TrawFish
## Model selected: Lin
## nugget = 0; sill = 0.03496; range = 3.90865; kappa = 0.5

NetFish
## Model selected: Exp
## nugget = 0; sill = 0.00405; range = 0.7045; kappa = 0.5

DredFish
## Model selected: Lin
## nugget = 0; sill = 0.0102; range = 2.82184; kappa = 0.5

Correlation coefficients between exposure indices and ecosystem variables
| aquaculture |
-0.1158 |
-0.02547 |
-0.04022 |
0.05245 |
-0.001245 |
-0.1348 |
-0.1808 |
-0.2441 |
-0.2756 |
-0.2226 |
-0.1868 |
-0.1541 |
-0.2108 |
-0.2589 |
0.214 |
0.01476 |
0.1318 |
0.00835 |
| city |
-0.1915 |
-0.1374 |
0.3251 |
-0.2108 |
-0.07314 |
-0.2814 |
-0.1124 |
-0.1374 |
0.09102 |
0.1144 |
-0.2531 |
-0.2167 |
-0.1365 |
0.022 |
-0.1389 |
0.08568 |
-0.1017 |
-0.01358 |
| dredging_collect |
0.1284 |
-0.04929 |
0.03491 |
0.007727 |
-0.03208 |
-0.02709 |
-0.07619 |
-0.007967 |
0.08903 |
0.443 |
0.1368 |
-0.07797 |
-0.04447 |
0.04908 |
-0.08664 |
-0.07784 |
0.01154 |
0.07244 |
| dredging_dump |
0.172 |
-0.04662 |
-0.1423 |
0.1796 |
-0.03045 |
0.49 |
0.0951 |
0.1621 |
0.1948 |
0.1584 |
0.1837 |
0.05096 |
0.1757 |
0.1812 |
-0.1103 |
-0.1077 |
0.001877 |
0.06612 |
| industry |
0.1108 |
-0.06908 |
0.1182 |
-0.08383 |
0.002292 |
0.2177 |
-0.08365 |
0.2081 |
0.346 |
0.5225 |
0.4589 |
-0.04507 |
0.08678 |
0.171 |
-0.2597 |
-0.1106 |
-0.1693 |
-0.06869 |
| shipping_mooring |
0.1507 |
-0.0584 |
-0.2178 |
0.2821 |
-0.07104 |
0.2276 |
0.3382 |
0.2542 |
0.2608 |
0.08722 |
0.1473 |
0.5368 |
0.3707 |
0.3189 |
0.04762 |
-0.02356 |
0.01182 |
-0.04485 |
| shipping_traffic |
0.2781 |
-0.1757 |
-0.1499 |
0.2059 |
0.04646 |
0.2906 |
0.12 |
0.2351 |
0.3716 |
0.4034 |
0.2098 |
0.2713 |
0.2493 |
0.3046 |
-0.07039 |
-0.1667 |
0.02405 |
0.04157 |
| sewers_rain |
0.2638 |
-0.03807 |
-0.3391 |
0.2332 |
0.208 |
0.6053 |
0.3381 |
0.5494 |
0.5711 |
0.3675 |
0.6572 |
0.2872 |
0.5263 |
0.4762 |
-0.2744 |
-0.02765 |
-0.2634 |
-0.1792 |
| sewers_waste |
0.2178 |
-0.01654 |
-0.2016 |
0.1443 |
0.109 |
0.5704 |
0.4656 |
0.5462 |
0.5874 |
0.3012 |
0.5258 |
0.3444 |
0.6146 |
0.5542 |
-0.3849 |
0.09536 |
-0.3498 |
-0.1482 |
| wharves_city |
-0.04686 |
-0.07177 |
0.156 |
-0.09151 |
-0.04696 |
-0.1338 |
-0.03555 |
0.03123 |
0.1656 |
0.1915 |
-0.04004 |
-0.1075 |
-0.04788 |
0.1061 |
-0.05345 |
-0.0373 |
-0.0008743 |
0.02854 |
| wharves_industry |
0.1701 |
-0.01676 |
0.04789 |
-0.02939 |
-0.01672 |
0.3624 |
-0.07242 |
0.2356 |
0.2978 |
0.6577 |
0.4764 |
0.01584 |
0.1617 |
0.1531 |
-0.3295 |
-0.1381 |
-0.2458 |
-0.08293 |
| fisheries_trap |
-0.2583 |
-0.04088 |
0.2419 |
-0.1873 |
-0.05337 |
-0.1959 |
-0.063 |
-0.1121 |
-0.0935 |
-0.09971 |
-0.1092 |
-0.1393 |
-0.1544 |
-0.1124 |
0.01116 |
0.05966 |
-0.02473 |
-0.04636 |
| fisheries_trawl |
-0.1915 |
0.2673 |
0.05775 |
-0.1588 |
-0.04853 |
-0.1297 |
-0.1941 |
-0.1716 |
-0.1947 |
-0.1103 |
-0.1688 |
-0.155 |
-0.1798 |
-0.1872 |
0.1712 |
0.05158 |
0.00763 |
-0.1071 |
| fisheries_net |
0.07494 |
-0.02727 |
-0.05045 |
0.07243 |
-0.01724 |
-0.002186 |
-0.01307 |
0.01643 |
0.01172 |
0.01391 |
0.01635 |
-0.01842 |
0.001042 |
0.003464 |
-0.01593 |
-0.03741 |
0.02955 |
0.03216 |
| fisheries_dredge |
-0.1612 |
-0.003513 |
0.2096 |
-0.1735 |
-0.05351 |
-0.2004 |
-0.2427 |
-0.3064 |
-0.3385 |
-0.2843 |
-0.2684 |
-0.2206 |
-0.2788 |
-0.3069 |
0.3319 |
0.01544 |
0.2737 |
0.1183 |
| cumulative_exposure |
0.2362 |
-0.1483 |
-0.09073 |
0.1678 |
-0.01221 |
0.4003 |
0.1526 |
0.3345 |
0.5125 |
0.5732 |
0.3907 |
0.2753 |
0.3375 |
0.4036 |
-0.1838 |
-0.1344 |
-0.1049 |
-0.04512 |

2. Covariation between exposure indices and ecosystem parameters
Several types of models were considered to explore relationships: linear, quadratic, exponential and logarithmic. The model with the highest \(R^{2}\) is presented on each plot.
⚠️ Only linear models were implemented for now, as there are some bugs with the calculation of the others.
AquaInf

CityInf

InduInf

CollDred

DumpDred

MoorShip

TrafShip

RainSew

WastSew

CityWha

InduWha

TrapFish

TrawFish

NetFish

DredFish

Cumulative exposure

3. Species abundances by cumulative exposure index
The following graphs present the distribution of sampled phyla along a gradient of cumulative exposure.

The threshold classification is based on the exposure index: the higher the index, the lower the status.
Phylum mean abundances by group
| Annelida |
8 |
15 |
28.6 |
41.7 |
29.4 |
| Arthropoda |
9.5 |
12.3 |
37 |
61.8 |
45.5 |
| Cnidaria |
0 |
0 |
0 |
0 |
0.0161 |
| Echinodermata |
0.5 |
1 |
0.115 |
5 |
3.92 |
| Mollusca |
24 |
21 |
7.19 |
8.4 |
16.9 |
| Nematoda |
0 |
0 |
0.423 |
1.8 |
16.2 |
| Nemertea |
0 |
0 |
0.154 |
0 |
0.194 |
| Sipuncula |
1 |
0 |
0.5 |
0.333 |
0.145 |

4. Regressions between exposure indices and community characteristics
4.1. Data manipulation
For the following analyses, independant variables are exposure indices, dependant variables are community characteristics. Variables have been standardized by mean and standard-deviation.
All stations and predictors were selected for the regressions, as we are interested in each of them.
4.2. Univariate regressions
We used linear models for the regressions on community characteristics. Variables have been standardized by mean and standard-deviation (coefficients need to be back-transformed to be used in predictive models).
We identified which variables were selected after an AIC procedure to predict the best the parameters. Results of the variable selection, according to AIC, are shown on the table below:
| AquaInf |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
| CityInf |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
| InduInf |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
| CollDred |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
| DumpDred |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
| MoorShip |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
| TrafShip |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
| RainSew |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
| WastSew |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
| CityWha |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
| InduWha |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
| TrapFish |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
| TrawFish |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
| NetFish |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
| DredFish |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
** ** |
| Adjusted \(R^{2}\) |
|
|
|
|
|
|
|
Details of the regressions, with diagnostics and cross-validation, are summarized below.
Richness
## FULL MODEL
## Adjusted R2 is: 0.19
Fitting linear model: S ~ aquaculture + city + dredging_collect + dredging_dump + industry + shipping_mooring + shipping_traffic + sewers_rain + sewers_waste + wharves_city + wharves_industry + fisheries_trap + fisheries_trawl + fisheries_net + fisheries_dredge
| (Intercept) |
3.756e-17 |
0.0865 |
4.342e-16 |
1 |
|
| aquaculture |
0.1492 |
0.09442 |
1.581 |
0.1174 |
|
| city |
-0.2279 |
0.191 |
-1.193 |
0.2359 |
|
| dredging_collect |
0.0811 |
0.1256 |
0.6457 |
0.5201 |
|
| dredging_dump |
-0.07032 |
0.09465 |
-0.743 |
0.4594 |
|
| industry |
0.4327 |
0.2262 |
1.913 |
0.05886 |
|
| shipping_mooring |
0.05063 |
0.1168 |
0.4336 |
0.6656 |
|
| shipping_traffic |
0.09784 |
0.1273 |
0.7689 |
0.444 |
|
| sewers_rain |
-0.1481 |
0.1735 |
-0.8533 |
0.3957 |
|
| sewers_waste |
-0.02823 |
0.152 |
-0.1856 |
0.8531 |
|
| wharves_city |
0.01368 |
0.1586 |
0.08629 |
0.9314 |
|
| wharves_industry |
-0.5888 |
0.2096 |
-2.809 |
0.00607 |
* * |
| fisheries_trap |
0.02205 |
0.1147 |
0.1923 |
0.8479 |
|
| fisheries_trawl |
0.1541 |
0.09521 |
1.619 |
0.1089 |
|
| fisheries_net |
-0.02756 |
0.0911 |
-0.3025 |
0.763 |
|
| fisheries_dredge |
0.2589 |
0.09578 |
2.704 |
0.008172 |
* * |
## RMSE from cross-validation: 74.49011
Variance Inflation Factors
| VIF |
1.09 |
2.2 |
1.45 |
1.09 |
2.6 |
1.34 |
1.46 |
2 |
1.75 |
1.82 |
2.41 |
1.32 |
1.1 |
1.05 |
1.1 |

## REDUCED MODEL
## Adjusted R2 is: 0.23
Fitting linear model: S ~ aquaculture + city + industry + sewers_rain + wharves_industry + fisheries_trawl + fisheries_dredge
| (Intercept) |
-1.518e-17 |
0.08451 |
-1.796e-16 |
1 |
|
| aquaculture |
0.1495 |
0.0894 |
1.672 |
0.09765 |
|
| city |
-0.1757 |
0.1051 |
-1.672 |
0.09767 |
|
| industry |
0.4391 |
0.1887 |
2.326 |
0.02202 |
* |
| sewers_rain |
-0.1721 |
0.1211 |
-1.421 |
0.1584 |
|
| wharves_industry |
-0.5534 |
0.1674 |
-3.306 |
0.001314 |
* * |
| fisheries_trawl |
0.147 |
0.08958 |
1.641 |
0.104 |
|
| fisheries_dredge |
0.2472 |
0.09106 |
2.715 |
0.007802 |
* * |
## RMSE from cross-validation: 0.9005653
Variance Inflation Factors
| VIF |
1.05 |
1.24 |
2.22 |
1.43 |
1.97 |
1.05 |
1.07 |

Density
## FULL MODEL
## Adjusted R2 is: -0.04
Fitting linear model: N ~ aquaculture + city + dredging_collect + dredging_dump + industry + shipping_mooring + shipping_traffic + sewers_rain + sewers_waste + wharves_city + wharves_industry + fisheries_trap + fisheries_trawl + fisheries_net + fisheries_dredge
| (Intercept) |
3.613e-16 |
0.09806 |
3.685e-15 |
1 |
|
| aquaculture |
0.04529 |
0.107 |
0.4231 |
0.6732 |
|
| city |
0.2669 |
0.2165 |
1.233 |
0.2208 |
|
| dredging_collect |
0.03992 |
0.1424 |
0.2804 |
0.7798 |
|
| dredging_dump |
-0.08565 |
0.1073 |
-0.7982 |
0.4268 |
|
| industry |
0.00836 |
0.2564 |
0.0326 |
0.9741 |
|
| shipping_mooring |
0.05349 |
0.1324 |
0.4041 |
0.6871 |
|
| shipping_traffic |
-0.1616 |
0.1443 |
-1.12 |
0.2654 |
|
| sewers_rain |
0.1503 |
0.1967 |
0.7638 |
0.4469 |
|
| sewers_waste |
0.1219 |
0.1724 |
0.7071 |
0.4813 |
|
| wharves_city |
-0.2007 |
0.1798 |
-1.117 |
0.267 |
|
| wharves_industry |
-0.2085 |
0.2377 |
-0.8772 |
0.3826 |
|
| fisheries_trap |
0.0419 |
0.13 |
0.3223 |
0.7479 |
|
| fisheries_trawl |
0.0994 |
0.1079 |
0.9209 |
0.3595 |
|
| fisheries_net |
-0.01414 |
0.1033 |
-0.1369 |
0.8914 |
|
| fisheries_dredge |
0.04752 |
0.1086 |
0.4377 |
0.6627 |
|
## RMSE from cross-validation: 67.53029
Variance Inflation Factors
| VIF |
1.09 |
2.2 |
1.45 |
1.09 |
2.6 |
1.34 |
1.46 |
2 |
1.75 |
1.82 |
2.41 |
1.32 |
1.1 |
1.05 |
1.1 |

## REDUCED MODEL
## Adjusted R2 is: 0.04
Fitting linear model: N ~ shipping_traffic + sewers_waste + wharves_industry
| (Intercept) |
2.523e-16 |
0.09417 |
2.679e-15 |
1 |
|
| shipping_traffic |
-0.1538 |
0.09713 |
-1.584 |
0.1163 |
|
| sewers_waste |
0.192 |
0.1038 |
1.849 |
0.06737 |
|
| wharves_industry |
-0.1829 |
0.1054 |
-1.736 |
0.08557 |
|
## RMSE from cross-validation: 1.024639
Variance Inflation Factors
| VIF |
1.03 |
1.1 |
1.11 |

Diversity
## FULL MODEL
## Adjusted R2 is: 0.13
Fitting linear model: H ~ aquaculture + city + dredging_collect + dredging_dump + industry + shipping_mooring + shipping_traffic + sewers_rain + sewers_waste + wharves_city + wharves_industry + fisheries_trap + fisheries_trawl + fisheries_net + fisheries_dredge
| (Intercept) |
5.367e-16 |
0.08997 |
5.966e-15 |
1 |
|
| aquaculture |
0.0483 |
0.09821 |
0.4918 |
0.624 |
|
| city |
-0.4247 |
0.1987 |
-2.138 |
0.0352 |
* |
| dredging_collect |
0.1413 |
0.1306 |
1.081 |
0.2824 |
|
| dredging_dump |
0.01613 |
0.09845 |
0.1639 |
0.8702 |
|
| industry |
0.4705 |
0.2353 |
2 |
0.04847 |
* |
| shipping_mooring |
-0.06062 |
0.1215 |
-0.4991 |
0.6189 |
|
| shipping_traffic |
0.1862 |
0.1324 |
1.407 |
0.1629 |
|
| sewers_rain |
-0.3528 |
0.1805 |
-1.955 |
0.05366 |
|
| sewers_waste |
0.02754 |
0.1582 |
0.1741 |
0.8622 |
|
| wharves_city |
0.1115 |
0.1649 |
0.676 |
0.5007 |
|
| wharves_industry |
-0.5602 |
0.218 |
-2.569 |
0.01181 |
* |
| fisheries_trap |
0.0004403 |
0.1193 |
0.003691 |
0.9971 |
|
| fisheries_trawl |
-0.04307 |
0.09903 |
-0.4349 |
0.6646 |
|
| fisheries_net |
0.008452 |
0.09476 |
0.0892 |
0.9291 |
|
| fisheries_dredge |
0.1905 |
0.09963 |
1.912 |
0.059 |
|
## RMSE from cross-validation: 3.365337
Variance Inflation Factors
| VIF |
1.09 |
2.2 |
1.45 |
1.09 |
2.6 |
1.34 |
1.46 |
2 |
1.75 |
1.82 |
2.41 |
1.32 |
1.1 |
1.05 |
1.1 |

## REDUCED MODEL
## Adjusted R2 is: 0.18
Fitting linear model: H ~ city + dredging_collect + industry + shipping_traffic + sewers_rain + wharves_industry + fisheries_dredge
| (Intercept) |
5.545e-16 |
0.08699 |
6.374e-15 |
1 |
|
| city |
-0.3272 |
0.1137 |
-2.878 |
0.004894 |
* * |
| dredging_collect |
0.1677 |
0.1102 |
1.522 |
0.1311 |
|
| industry |
0.4759 |
0.1927 |
2.47 |
0.0152 |
* |
| shipping_traffic |
0.158 |
0.09467 |
1.669 |
0.09818 |
|
| sewers_rain |
-0.3095 |
0.1258 |
-2.46 |
0.0156 |
* |
| wharves_industry |
-0.5618 |
0.1791 |
-3.137 |
0.002243 |
* * |
| fisheries_dredge |
0.2123 |
0.09302 |
2.282 |
0.0246 |
* |
## RMSE from cross-validation: 0.9913484
Variance Inflation Factors
| VIF |
1.3 |
1.26 |
2.2 |
1.08 |
1.44 |
2.05 |
1.06 |

Evenness
## FULL MODEL
## Adjusted R2 is: -0.02
Fitting linear model: J ~ aquaculture + city + dredging_collect + dredging_dump + industry + shipping_mooring + shipping_traffic + sewers_rain + sewers_waste + wharves_city + wharves_industry + fisheries_trap + fisheries_trawl + fisheries_net + fisheries_dredge
| (Intercept) |
-4.173e-17 |
0.09741 |
-4.284e-16 |
1 |
|
| aquaculture |
-0.06583 |
0.1063 |
-0.6192 |
0.5373 |
|
| city |
-0.3493 |
0.2151 |
-1.624 |
0.1078 |
|
| dredging_collect |
0.116 |
0.1414 |
0.8198 |
0.4144 |
|
| dredging_dump |
0.05936 |
0.1066 |
0.5569 |
0.5789 |
|
| industry |
0.1579 |
0.2547 |
0.6198 |
0.5369 |
|
| shipping_mooring |
-0.1499 |
0.1315 |
-1.14 |
0.2573 |
|
| shipping_traffic |
0.1542 |
0.1433 |
1.076 |
0.2847 |
|
| sewers_rain |
-0.3763 |
0.1954 |
-1.925 |
0.05727 |
|
| sewers_waste |
0.08788 |
0.1712 |
0.5132 |
0.609 |
|
| wharves_city |
0.1238 |
0.1786 |
0.6933 |
0.4899 |
|
| wharves_industry |
-0.185 |
0.2361 |
-0.7835 |
0.4353 |
|
| fisheries_trap |
-0.02202 |
0.1291 |
-0.1705 |
0.865 |
|
| fisheries_trawl |
-0.1756 |
0.1072 |
-1.637 |
0.105 |
|
| fisheries_net |
0.0213 |
0.1026 |
0.2077 |
0.836 |
|
| fisheries_dredge |
0.05376 |
0.1079 |
0.4984 |
0.6194 |
|
## RMSE from cross-validation: 100.5167
Variance Inflation Factors
| VIF |
1.09 |
2.2 |
1.45 |
1.09 |
2.6 |
1.34 |
1.46 |
2 |
1.75 |
1.82 |
2.41 |
1.32 |
1.1 |
1.05 |
1.1 |

## REDUCED MODEL
## Adjusted R2 is: 0.05
Fitting linear model: J ~ city + shipping_mooring + shipping_traffic + sewers_rain + fisheries_trawl
| (Intercept) |
-1.498e-16 |
0.09403 |
-1.593e-15 |
1 |
|
| city |
-0.168 |
0.1071 |
-1.569 |
0.1198 |
|
| shipping_mooring |
-0.174 |
0.1123 |
-1.549 |
0.1245 |
|
| shipping_traffic |
0.1939 |
0.1177 |
1.648 |
0.1024 |
|
| sewers_rain |
-0.2968 |
0.1068 |
-2.778 |
0.006505 |
* * |
| fisheries_trawl |
-0.1724 |
0.09938 |
-1.735 |
0.08583 |
|
## RMSE from cross-validation: 1.077156
Variance Inflation Factors
| VIF |
1.13 |
1.19 |
1.25 |
1.13 |
1.05 |

Annelids
## FULL MODEL
## McFadden's pseudo-R2 is: 0.11
Fitting generalized (poisson/log) linear model: annelids ~ aquaculture + city + dredging_collect + dredging_dump + industry + shipping_mooring + shipping_traffic + sewers_rain + sewers_waste + wharves_city + wharves_industry + fisheries_trap + fisheries_trawl + fisheries_net + fisheries_dredge
| (Intercept) |
3.327 |
0.01918 |
173.5 |
0 |
* * * |
| aquaculture |
0.1188 |
0.01618 |
7.346 |
2.036e-13 |
* * * |
| city |
-0.006262 |
0.04007 |
-0.1563 |
0.8758 |
|
| dredging_collect |
-0.08911 |
0.02979 |
-2.992 |
0.002775 |
* * |
| dredging_dump |
-0.09399 |
0.02678 |
-3.51 |
0.0004481 |
* * * |
| industry |
0.1312 |
0.05177 |
2.534 |
0.01126 |
* |
| shipping_mooring |
0.1237 |
0.02257 |
5.483 |
4.187e-08 |
* * * |
| shipping_traffic |
-0.1175 |
0.02577 |
-4.56 |
5.124e-06 |
* * * |
| sewers_rain |
-0.007578 |
0.03741 |
-0.2025 |
0.8395 |
|
| sewers_waste |
0.1423 |
0.034 |
4.186 |
2.834e-05 |
* * * |
| wharves_city |
0.09572 |
0.02678 |
3.574 |
0.000351 |
* * * |
| wharves_industry |
-0.3646 |
0.0562 |
-6.488 |
8.7e-11 |
* * * |
| fisheries_trap |
0.02175 |
0.02053 |
1.059 |
0.2894 |
|
| fisheries_trawl |
-0.1876 |
0.03243 |
-5.786 |
7.217e-09 |
* * * |
| fisheries_net |
-0.03257 |
0.02348 |
-1.387 |
0.1653 |
|
| fisheries_dredge |
-0.05999 |
0.02418 |
-2.481 |
0.01311 |
* |
## Unbiased RMSE from cross-validation: 38.57226
Variance Inflation Factors
| VIF |
1.16 |
2.48 |
1.21 |
1.04 |
2.35 |
1.4 |
1.41 |
1.84 |
1.86 |
2.05 |
2.13 |
1.62 |
1.09 |
1.03 |
1.15 |

## REDUCED MODEL
## McFadden's pseudo-R2 is: 0.11
Fitting generalized (poisson/log) linear model: annelids ~ aquaculture + dredging_collect + dredging_dump + industry + shipping_mooring + shipping_traffic + sewers_waste + wharves_city + wharves_industry + fisheries_trawl + fisheries_net + fisheries_dredge
| (Intercept) |
3.327 |
0.01917 |
173.6 |
0 |
* * * |
| aquaculture |
0.122 |
0.01579 |
7.726 |
1.11e-14 |
* * * |
| dredging_collect |
-0.09987 |
0.02712 |
-3.682 |
0.0002311 |
* * * |
| dredging_dump |
-0.09135 |
0.0264 |
-3.46 |
0.0005393 |
* * * |
| industry |
0.1326 |
0.04374 |
3.031 |
0.002438 |
* * |
| shipping_mooring |
0.1269 |
0.02164 |
5.864 |
4.513e-09 |
* * * |
| shipping_traffic |
-0.1261 |
0.02378 |
-5.302 |
1.147e-07 |
* * * |
| sewers_waste |
0.1385 |
0.02244 |
6.174 |
6.642e-10 |
* * * |
| wharves_city |
0.111 |
0.01468 |
7.563 |
3.933e-14 |
* * * |
| wharves_industry |
-0.3651 |
0.05007 |
-7.291 |
3.086e-13 |
* * * |
| fisheries_trawl |
-0.1858 |
0.03214 |
-5.78 |
7.46e-09 |
* * * |
| fisheries_net |
-0.03143 |
0.02322 |
-1.354 |
0.1758 |
|
| fisheries_dredge |
-0.05812 |
0.02396 |
-2.426 |
0.01526 |
* |
## Unbiased RMSE from cross-validation: 40.88161
Variance Inflation Factors
| VIF |
1.13 |
1.11 |
1.02 |
1.99 |
1.34 |
1.3 |
1.23 |
1.12 |
1.89 |
1.08 |
1.02 |
1.14 |

Arthropods
## FULL MODEL
## McFadden's pseudo-R2 is: 0.25
Fitting generalized (poisson/log) linear model: arthropods ~ aquaculture + city + dredging_collect + dredging_dump + industry + shipping_mooring + shipping_traffic + sewers_rain + sewers_waste + wharves_city + wharves_industry + fisheries_trap + fisheries_trawl + fisheries_net + fisheries_dredge
| (Intercept) |
3.566 |
0.01774 |
201 |
0 |
* * * |
| aquaculture |
0.001736 |
0.02192 |
0.07922 |
0.9369 |
|
| city |
0.2493 |
0.02899 |
8.599 |
8.065e-18 |
* * * |
| dredging_collect |
0.06636 |
0.03109 |
2.134 |
0.03283 |
* |
| dredging_dump |
-0.2278 |
0.03006 |
-7.58 |
3.468e-14 |
* * * |
| industry |
0.2236 |
0.04455 |
5.018 |
5.212e-07 |
* * * |
| shipping_mooring |
0.1898 |
0.01885 |
10.07 |
7.635e-24 |
* * * |
| shipping_traffic |
-0.2288 |
0.02117 |
-10.81 |
3.149e-27 |
* * * |
| sewers_rain |
0.3584 |
0.02368 |
15.13 |
9.583e-52 |
* * * |
| sewers_waste |
0.4245 |
0.02501 |
16.98 |
1.244e-64 |
* * * |
| wharves_city |
-0.2906 |
0.03567 |
-8.145 |
3.782e-16 |
* * * |
| wharves_industry |
-0.6805 |
0.0462 |
-14.73 |
4.195e-49 |
* * * |
| fisheries_trap |
-0.03652 |
0.01785 |
-2.046 |
0.04072 |
* |
| fisheries_trawl |
0.1233 |
0.01579 |
7.811 |
5.668e-15 |
* * * |
| fisheries_net |
-0.03258 |
0.02067 |
-1.576 |
0.115 |
|
| fisheries_dredge |
0.1307 |
0.01364 |
9.581 |
9.595e-22 |
* * * |
## Unbiased RMSE from cross-validation: 247.6144
Variance Inflation Factors
| VIF |
1.07 |
2.04 |
1.3 |
1.02 |
2.72 |
1.36 |
1.33 |
1.82 |
1.96 |
1.53 |
2.61 |
1.12 |
1.12 |
1.02 |
1.1 |

## REDUCED MODEL
## McFadden's pseudo-R2 is: 0.25
Fitting generalized (poisson/log) linear model: arthropods ~ city + dredging_collect + dredging_dump + industry + shipping_mooring + shipping_traffic + sewers_rain + sewers_waste + wharves_city + wharves_industry + fisheries_trap + fisheries_trawl + fisheries_net + fisheries_dredge
| (Intercept) |
3.566 |
0.01774 |
201 |
0 |
* * * |
| city |
0.2491 |
0.0289 |
8.622 |
6.607e-18 |
* * * |
| dredging_collect |
0.06645 |
0.03107 |
2.139 |
0.03246 |
* |
| dredging_dump |
-0.2279 |
0.03006 |
-7.582 |
3.408e-14 |
* * * |
| industry |
0.2228 |
0.04355 |
5.116 |
3.118e-07 |
* * * |
| shipping_mooring |
0.1896 |
0.01866 |
10.16 |
2.977e-24 |
* * * |
| shipping_traffic |
-0.2287 |
0.02116 |
-10.81 |
3.139e-27 |
* * * |
| sewers_rain |
0.3584 |
0.02367 |
15.14 |
9.297e-52 |
* * * |
| sewers_waste |
0.4243 |
0.02487 |
17.06 |
2.93e-65 |
* * * |
| wharves_city |
-0.2905 |
0.03566 |
-8.146 |
3.747e-16 |
* * * |
| wharves_industry |
-0.6798 |
0.04545 |
-14.96 |
1.417e-50 |
* * * |
| fisheries_trap |
-0.03635 |
0.01771 |
-2.052 |
0.04018 |
* |
| fisheries_trawl |
0.1231 |
0.01561 |
7.885 |
3.145e-15 |
* * * |
| fisheries_net |
-0.03263 |
0.02066 |
-1.579 |
0.1142 |
|
| fisheries_dredge |
0.1307 |
0.01364 |
9.586 |
9.155e-22 |
* * * |
## Unbiased RMSE from cross-validation: 119.3895
Variance Inflation Factors
| VIF |
2.03 |
1.3 |
1.02 |
2.66 |
1.34 |
1.33 |
1.82 |
1.95 |
1.53 |
2.57 |
1.11 |
1.1 |
1.02 |
1.1 |

Molluscs
## FULL MODEL
## McFadden's pseudo-R2 is: 0.27
Fitting generalized (poisson/log) linear model: molluscs ~ aquaculture + city + dredging_collect + dredging_dump + industry + shipping_mooring + shipping_traffic + sewers_rain + sewers_waste + wharves_city + wharves_industry + fisheries_trap + fisheries_trawl + fisheries_net + fisheries_dredge
| (Intercept) |
2.401 |
0.03209 |
74.82 |
0 |
* * * |
| aquaculture |
0.1329 |
0.02251 |
5.902 |
3.595e-09 |
* * * |
| city |
0.4958 |
0.06196 |
8.001 |
1.234e-15 |
* * * |
| dredging_collect |
0.0555 |
0.03201 |
1.734 |
0.08292 |
|
| dredging_dump |
-0.1538 |
0.05527 |
-2.783 |
0.005385 |
* * |
| industry |
0.464 |
0.06055 |
7.663 |
1.82e-14 |
* * * |
| shipping_mooring |
-0.02887 |
0.04629 |
-0.6237 |
0.5328 |
|
| shipping_traffic |
-0.1967 |
0.04477 |
-4.394 |
1.111e-05 |
* * * |
| sewers_rain |
0.01542 |
0.05418 |
0.2847 |
0.7759 |
|
| sewers_waste |
-0.4035 |
0.05628 |
-7.169 |
7.542e-13 |
* * * |
| wharves_city |
-0.3381 |
0.04519 |
-7.482 |
7.329e-14 |
* * * |
| wharves_industry |
-0.3206 |
0.06183 |
-5.185 |
2.156e-07 |
* * * |
| fisheries_trap |
0.0924 |
0.02728 |
3.387 |
0.0007066 |
* * * |
| fisheries_trawl |
0.09371 |
0.02449 |
3.826 |
0.0001305 |
* * * |
| fisheries_net |
0.06714 |
0.027 |
2.486 |
0.0129 |
* |
| fisheries_dredge |
0.12 |
0.01743 |
6.887 |
5.696e-12 |
* * * |
## Unbiased RMSE from cross-validation: 87.68681
Variance Inflation Factors
| VIF |
1.14 |
2.71 |
1.72 |
1.01 |
2.38 |
1.24 |
1.53 |
1.68 |
1.73 |
2.09 |
2.03 |
1.27 |
1.1 |
1.08 |
1.09 |

## REDUCED MODEL
## McFadden's pseudo-R2 is: 0.25
Fitting generalized (poisson/log) linear model: arthropods ~ city + dredging_collect + dredging_dump + industry + shipping_mooring + shipping_traffic + sewers_rain + sewers_waste + wharves_city + wharves_industry + fisheries_trap + fisheries_trawl + fisheries_net + fisheries_dredge
| (Intercept) |
3.566 |
0.01774 |
201 |
0 |
* * * |
| city |
0.2491 |
0.0289 |
8.622 |
6.607e-18 |
* * * |
| dredging_collect |
0.06645 |
0.03107 |
2.139 |
0.03246 |
* |
| dredging_dump |
-0.2279 |
0.03006 |
-7.582 |
3.408e-14 |
* * * |
| industry |
0.2228 |
0.04355 |
5.116 |
3.118e-07 |
* * * |
| shipping_mooring |
0.1896 |
0.01866 |
10.16 |
2.977e-24 |
* * * |
| shipping_traffic |
-0.2287 |
0.02116 |
-10.81 |
3.139e-27 |
* * * |
| sewers_rain |
0.3584 |
0.02367 |
15.14 |
9.297e-52 |
* * * |
| sewers_waste |
0.4243 |
0.02487 |
17.06 |
2.93e-65 |
* * * |
| wharves_city |
-0.2905 |
0.03566 |
-8.146 |
3.747e-16 |
* * * |
| wharves_industry |
-0.6798 |
0.04545 |
-14.96 |
1.417e-50 |
* * * |
| fisheries_trap |
-0.03635 |
0.01771 |
-2.052 |
0.04018 |
* |
| fisheries_trawl |
0.1231 |
0.01561 |
7.885 |
3.145e-15 |
* * * |
| fisheries_net |
-0.03263 |
0.02066 |
-1.579 |
0.1142 |
|
| fisheries_dredge |
0.1307 |
0.01364 |
9.586 |
9.155e-22 |
* * * |
## Unbiased RMSE from cross-validation: 156.6728
Variance Inflation Factors
| VIF |
2.03 |
1.3 |
1.02 |
2.66 |
1.34 |
1.33 |
1.82 |
1.95 |
1.53 |
2.57 |
1.11 |
1.1 |
1.02 |
1.1 |

Body: non-calcifying
Body: chitinous
Body: aragonite
Body: calcite
Body: calcareous
Size: small
Size: medium
Size: large
Food: grazers
Food: predators
Food: scavengers
Food: filter feeders
Food: surface deposit feeders
Food: subsurface deposit feeders
Food: parasites
Lifestyle: mobile
Lifestyle: sessile
Lifestyle: burrower
Lifestyle: crawler
Lifestyle: swimmer
Lifestyle: tubicolous
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